Large-scale multiethnic electronic health record resource for diabetes complications research: the North West London Diabetes Cohort (NWLDC) - cohort profile.

PURPOSE: The North West London Diabetes Cohort is established to provide systematic characterisation of a large diabetes population as a foundation for complications research and prognostic modelling. Many predictive modelling studies neglect the essential descriptive characterisation of underlying cohorts, focusing narrowly on model accuracy. This cohort profile addresses this gap by comprehensively describing the demographic composition, clinical characteristics and complication incidence patterns. The notably diverse, multiethnic population enables examination of ethnic disparities and supports future development of reliable prognostic models and evidence-based prevention strategies for diabetes complications. PARTICIPANTS: At baseline, 337 271 patients with diabetes were identified. It includes 279 067 patients with type 2 diabetes, 17 638 with type 1 diabetes, 33 590 with gestational diabetes and 6916 with unspecified diabetes. The earliest diabetes diagnosis dates to January 1932, with data updated to 27 May 2025. FINDINGS TO DATE: This cohort profile describes baseline characteristics of patients with comprehensive data collected on demographics (age, sex, Deprivation Index, ethnicity), clinical measures (glycated haemoglobin, body mass index, blood pressure, lipids and estimated glomerular filtration rate) and 14 major diabetes complications tracked longitudinally. Key findings for patients with type 2 diabetes reveal diabetic retinopathy as the most common complication (74.6 per 1000 person-years), followed by hypertension (51.0) and kidney disease (31.4). Cumulative incidence analyses using the Aalen-Johansen estimator, which accounts for mortality as a competing risk, demonstrated significant ethnic disparities, with black, Asian, mixed and other ethnic groups showing elevated risk compared with white patients. Time-varying Cox models identified strong clustering between cardiovascular and renal complications, confirming a cardiometabolic-renal syndrome. Mental health conditions (depression and anxiety) were prevalent throughout the disease timeline, occurring both before and after diabetes diagnosis. FUTURE PLANS: This cohort will be used as a platform for developing and validating prognostic models for diabetes complications, enabling risk stratification and targeted interventions. Future work will incorporate medication data to refine diabetes type classification, examine the effectiveness of antidiabetic medications in preventing different complications and address demographic differences in prognostic model performance and prediction accuracy. To better characterise lifestyle, further interrogation of electronic health record data will examine recording of advice given, including dietary advice, referral to weight management schemes and presence of alcohol consumption codes.